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Related papers: Uncertainty Quantification in Hierarchical Vehicul…

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We present a method to quantify uncertainty in the predictions made by simulations of mathematical models that can be applied to a broad class of stochastic, discrete, and differential equation models. Quantifying uncertainty is crucial for…

Machine Learning · Statistics 2015-03-05 Kyle S. Hickmann , James M. Hyman , Sara Y. Del Valle

Models under location uncertainty are derived assuming that a component of the velocity is uncorrelated in time. The material derivative is accordingly modified to include an advection correction, inhomogeneous and anisotropic diffusion…

Atmospheric and Oceanic Physics · Physics 2017-05-31 Valentin Resseguier , Etienne Memin , Bertrand Chapron

This article is an invitation. It is, first, an invitation to consider as a subject worthy of attention the wide range of situations where small discrete elements, either bubbles, droplets or solid particles, are embedded in turbulent…

Fluid Dynamics · Physics 2023-11-06 Jean-Pierre Minier , Christophe Henry

We present a derivation of a stochastic model of Navier Stokes equations that relies on a decomposition of the velocity fields into a differentiable drift component and a time uncorrelated uncertainty random term. This type of decomposition…

Fluid Dynamics · Physics 2015-06-15 Etienne Mémin

The present research article is devoted to the study of two fluid-dynamical traffic models and their steady states by first analyzing the kinetic-type Borsche-Kimathi-Klar model and the Navier-Stokes-type Helbing model. To fulfill this…

Physics and Society · Physics 2018-02-16 M David Alvarez Hernandez , Shani Alvarez Hernandez

To date no satisfying model exists to explain the mean velocity profile within the whole turbulent layer of canonical wall bounded flows. We propose a modification of the velocity profile expression that ensues from a recently proposed…

Fluid Dynamics · Physics 2018-12-10 Benoit Pinier , Etienne Mémin , Sylvain Laizet , Roger Lewandowski

We analyze the transport properties of a low density ensemble of identical macroscopic particles immersed in an active fluid. The particles are modeled as inelastic hard spheres (granular gas). The non-homogeneous active fluid is modeled by…

Soft Condensed Matter · Physics 2017-10-17 Francisco Vega Reyes , Antonio Lasanta

Modeling car-following behavior is fundamental to microscopic traffic simulation, yet traditional deterministic models often fail to capture the full extent of variability and unpredictability in human driving. While many modern approaches…

Applications · Statistics 2026-01-30 Chengyuan Zhang , Zhengbing He , Cathy Wu , Lijun Sun

Most car-following models show a transition from laminar to ``congested'' flow and vice versa. Deterministic models often have a density range where a disturbance needs a sufficiently large critical amplitude to move the flow from the…

Statistical Mechanics · Physics 2007-05-23 Kai Nagel , Christopher Kayatz , Peter Wagner

A kinetic model for granular mixtures is considered to study three different non-equilibrium situations. The model is based on the equivalence between a gas of elastic hard spheres subjected to a drag force proportional to the particle…

Soft Condensed Matter · Physics 2025-02-27 Pablo Avilés , David González Méndez , Vicente Garzó

An approach to the description of kinetics which taking into account the large-scale hydrodynamic transport processes for quantum Bose system is proposed. The nonequilibrium statistical operator which consistently describes both the kinetic…

Statistical Mechanics · Physics 2011-12-30 P. A. Hlushak , M. V. Tokarchuk

The balanced vehicular traffic model is a macroscopic model for vehicular traffic flow. We use this model to study the traffic dynamics at highway bottlenecks either caused by the restriction of the number of lanes or by on-ramps or…

Physics and Society · Physics 2007-05-23 Florian Siebel , Wolfram Mauser , Salissou Moutari , Michel Rascle

We propose a model uncertainty approach to heavy traffic asymptotics that allows for a high level of uncertainty. That is, the uncertainty classes of underlying distributions accommodate disturbances that are of order 1 at the usual…

Probability · Mathematics 2022-04-13 Rami Atar , Eyal Castiel , Yonatan Shadmi

In this paper we study model reduction of linear and bilinear quadratic stochastic control problems with parameter uncertainties. Specifically, we consider slow-fast systems with unknown diffusion coefficient and study the convergence of…

Optimization and Control · Mathematics 2021-02-10 Hafida Bouanani , Carsten Hartmann , Omar Kebiri

In this work, we show that the inverse-$\lambda$ shape in the fundamental diagram of traffic flow can be produced dynamically by a simple nonlinear mesoscopic model with stochastic noises. The proposed model is based on the gas-kinetic…

Physics and Society · Physics 2017-09-28 Wei-Liang Qian , Adriano F. Siqueira , Romuel F. Machado , Kai Lin , Ted William Grant

We consider the linearized BGK equation and want to quantify uncertainties in the case of modelling errors. More specifically, we want to quantify the error produced if the pre-determined equilibrium function is chosen inaccurately. In this…

Analysis of PDEs · Mathematics 2018-10-23 C. Klingenberg , Q. Li , M. Pirner

Many features of granular media can be modelled as a fluid of hard spheres with {\em inelastic} collisions. Under rapid flow conditions, the macroscopic behavior of grains can be described through hydrodynamic equations. At low-density, a…

Statistical Mechanics · Physics 2009-11-13 Vicente Garzo

A chain of kinetic equations for non-equilibrium one-particle, two-particle and $ s $-particle distribution functions of particles which take into account nonlinear hydrodynamic fluctuations is proposed. The method of Zubarev…

Statistical Mechanics · Physics 2017-02-13 I. R. Yukhnovskii , P. A. Hlushak , M. V. Tokarchuk

We overview some recent results in the field of uncertainty quantification for kinetic equations and related problems with random inputs. Uncertainties may be due to various reasons, such as lack of knowledge on the microscopic interaction…

Numerical Analysis · Mathematics 2020-04-13 Lorenzo Pareschi

Kinetically-constrained models are lattice-gas models that are used for describing glassy systems. By construction, their equilibrium state is trivial and there are no equal-time correlations between the occupancy of different sites. We…

Statistical Mechanics · Physics 2017-03-01 Eial Teomy , Yair Shokef